Read Me for 

Jan K. Brueckner, Shihe Fu, Yizhen Gu and Junfu Zhang, "Measuring the Stringency of Land-Use Regulation: The Case of China's Building-Height Limits," Review of Economics and Statistics, Forthcoming


All data and do files listed below are in STATA 14 format, except that landdata.dta and cleanlanddata.do are in STATA 13 format.

I. Stata data files

For Intercity Analysis:

* landdata.dta: Original land auction data, a proprietary data product assembled by the consulting firm--the China Index Academy.

* citylevelupdated_2.dta: Characteristics of prefectural level cities for 2000-2011, from the 2001-2012 editions of the China Urban Statistical Yearbook.

* CleanedLandData.dta: Cleaned land data are merged with city level characteristics from citylevelupdated_2.dta, which are then saved in this data file for empirical analysis.

* YearlyCharacteristicsForRESTatRR.dta: Yearly city characteristics, collected from various sources, except that the Bartik indexes are calculated by bartikindex.do.

* CityCharacteristicsForRESTatRR.dta: Cross-sectional city characteristics, collected from various sources, except that the Bartik indexes (in 2005) are calculated by bartikindex.do.

* CityYearsbook_1999_2011.dta: Annual city level data, collected from the China Urban Statistical Yearbook, which are used by bartikindex.do to calculate four different versions of the Bartik Index for all cities over different years. 

For Beijing Analysis:

* BeijingResidentialLandData.dta: From the CleanedLandData.dta, the 327 observations in Beijing are extracted and saved as this separate data file.

* SiteAttributes.dta: For each of the 327 land sales in BeijingResidentialLandData.dta, �parcelid� is used to find the online map for the location of this parcel, which is done manually. The locational information is then used to generate site attributes for each parcel, which are saved in this data file.

* zoning99newest.dta: Proprietary data constructed using two waves of detailed planning data from Beijing. Land parcels in central districts of Beijing are covered. For each parcel of land, planned FAR in 1999 and 2006 as well as detailed site attributes are available.


II. Stata programs

For Intercity Analysis:

* cleanlanddata.do: This program cleans the original land auction data, landdata.dta. New variables are constructed, merged with city level characteristics, and saved as CleanedLandData.dta for empirical analysis.
  - A block of code is written to do the following: After the land data are cleaned and before dropping outliers, keep all of the land transactions in the city of Beijing for a separate analysis, save these data as BeijingLandData.dta. This block of code is still in the do file but is commented out.
  - Another block of code is written to do the following: After the land data are cleaned and before dropping outliers, keep all observations for residential land sales to be used for the matched-pairs analysis, save these data as ResidentialLandSales.dta. This block of code is still in the do file but is commented out.
  - A third block of code is written to do the following: After the land data are cleaned and before dropping outliers, keep all observations for commercial land sales to be used for the matched-pairs analysis, save these data as CommercialLandSales.dta. This block of code is still in the do file but is commented out.
  - At the very end, this do file saved ResidentialMeanFAR.dta, which is used to draw the map in Figure 1.

* AnalyzeLandData.do: Use CleanedLandData.dta (cleaned land data merged with city characteristics) to perform cross city regression analysis. Results are in Table 1, panels A &B of Table 2, Table 3, and Appendix Tables A-1 and A-2.

* StringencyRegression.do: A separate do file called by AnalyzeLandData.do to perform the stringency regression analysis presented in Table 3. It uses dependent variables generated from regressions in AnalyzeLandData.do and MatchedPairs.do. The independent variables are city characteristics from citylevelupdated_2.dta.

* BoE_Calculation.do: Perform a back-of-envelope calculation (results in section 5.6).

* MatchedPairs.do: Identify clusters and run the log-log regressions controlling for cluster fixed effects (results in panels C&D of Table 2, panels (iii)-(iv) of Figue 2, and Appendix Table A-1).

* bartikindex.do: Use annual city level data hand collected from the China Urban Statistical Yearbook to calculate four different versions of the Bartik Index for all cities over different years.

For Beijing Analysis:

* BeiJing.do: Merge BeijingResidentialLandData.dta with SiteAttributes.dta and perform regression analysis (results in Table 4).

* dpdDataAnalysis.do: Use the detailed planning data in zoning99newest.dta to perform empirical analysis (results in Tables 5 and 6).

III. Data Accessibility

The land auction dataset we used, landdata.dta, is a proprietary data product assembled by the independent property research organization, the China Index Academy. A non-disclosure agreement precludes us from sharing the data on the ReStat website. Researchers can contact the data vendor directly for access to the database. See their contact information here: http://industry.fang.com/en/default.html.

The detailed planning data, zoning99newest.dta, are constructed using two waves of administrative data from the Beijing Institute of City Planning. The data use agreement does not allow us to post the data on the ReStat website. Researchers who need to access these data can send their request to Dr. Yizhen Gu (yizhengu@jnu.edu.cn), who could help forward the request to the Beijing Institute.

Thus landdata.dta, zoning99newest.dta, and the analysis samples constructed using these data are not posted here. All other data we used and all the STATA programs are in this archive.



